from fastai.vision.all import *
import gradio as gr

learn = load_learner('export.pkl')

labels = learn.dls.vocab

def predict(img):
    img = PILImage.create(img)
    pred, pred_ind, probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(probs))}

subfolder = Path('samples')
search_pattern = str(subfolder/'*.jpg')
jpg_files = glob.glob(search_pattern)

gr.Interface(fn=predict,
             inputs='image',
             outputs='label',
             examples=jpg_files,
             examples_per_page=10,
             live=True
            ).launch()